| ℓ2,1-Norm regularized discriminative feature selection for unsupervised learning Y Yang, HT Shen, Z Ma, Z Huang, X Zhou IJCAI international joint conference on artificial intelligence, 2011 | 1039 | 2011 |
| Multi-class active learning by uncertainty sampling with diversity maximization Y Yang, Z Ma, F Nie, X Chang, AG Hauptmann International Journal of Computer Vision 113, 113-127, 2015 | 531 | 2015 |
| Bi-level semantic representation analysis for multimedia event detection X Chang, Z Ma, Y Yang, Z Zeng, AG Hauptmann IEEE transactions on cybernetics 47 (5), 1180-1197, 2016 | 246 | 2016 |
| Feature Selection for Multimedia Analysis by Sharing Information among Multiple Tasks Y Yang, Z Ma, A Hauptmann, N Sebe IEEE, 2011 | 222 | 2011 |
| Semisupervised feature selection via spline regression for video semantic recognition Y Han, Y Yang, Y Yan, Z Ma, N Sebe, X Zhou IEEE Transactions on Neural Networks and Learning Systems 26 (2), 252-264, 2014 | 218 | 2014 |
| Web image annotation via subspace-sparsity collaborated feature selection Z Ma, F Nie, Y Yang, JRR Uijlings, N Sebe IEEE Transactions on Multimedia 14 (4), 1021-1030, 2012 | 215 | 2012 |
| Feature interaction augmented sparse learning for fast kinect motion detection X Chang, Z Ma, M Lin, Y Yang, AG Hauptmann IEEE transactions on image processing 26 (8), 3911-3920, 2017 | 209 | 2017 |
| Multitask Spectral Clustering by Exploring Intertask Correlation Y Yang, Z Ma, Y Yang, F Nie, HT Shen IEEE Transactions on Cybernetics, 2014 | 187 | 2014 |
| Multi-feature fusion via hierarchical regression for multimedia analysis Y Yang, J Song, Z Huang, Z Ma, N Sebe, AG Hauptmann IEEE Transactions on Multimedia 15 (3), 572-581, 2012 | 181 | 2012 |
| Discriminating joint feature analysis for multimedia data understanding Z Ma, F Nie, Y Yang, JRR Uijlings, N Sebe, AG Hauptmann IEEE Transactions on Multimedia 14 (6), 1662-1672, 2012 | 170 | 2012 |
| Knowledge adaptation for ad hoc multimedia event detection with few exemplars Z Ma, Y Yang, Y Cai, N Sebe, AG Hauptmann Proceedings of the 20th ACM international conference on Multimedia, 469-478, 2012 | 99 | 2012 |
| Knowledge adaptation with partiallyshared features for event detectionusing few exemplars Z Ma, Y Yang, N Sebe, AG Hauptmann IEEE transactions on pattern analysis and machine intelligence 36 (9), 1789-1802, 2014 | 94 | 2014 |
| Complex event detection via multi-source video attributes Z Ma, Y Yang, Z Xu, S Yan, N Sebe, AG Hauptmann Proceedings of the IEEE conference on Computer Vision and Pattern …, 2013 | 84 | 2013 |
| Semi-supervised multiple feature analysis for action recognition S Wang, Z Ma, Y Yang, X Li, C Pang, AG Hauptmann IEEE transactions on multimedia 16 (2), 289-298, 2013 | 79 | 2013 |
| Exploiting the entire feature space with sparsity for automatic image annotation Z Ma, Y Yang, F Nie, J Uijlings, N Sebe Proceedings of the 19th ACM international conference on Multimedia, 283-292, 2011 | 79 | 2011 |
| Multimedia event detection using a classifier-specific intermediate representation Z Ma, Y Yang, N Sebe, K Zheng, AG Hauptmann IEEE Transactions on Multimedia 15 (7), 1628-1637, 2013 | 75 | 2013 |
| The many shades of negativity Z Ma, X Chang, Y Yang, N Sebe, AG Hauptmann IEEE Transactions on Multimedia 19 (7), 1558-1568, 2017 | 69 | 2017 |
| How related exemplars help complex event detection in web videos? Y Yang, Z Ma, Z Xu, S Yan, AG Hauptmann Proceedings of the IEEE International Conference on Computer Vision, 2104-2111, 2013 | 60 | 2013 |
| Event-based media processing and analysis: A survey of the literature C Tzelepis, Z Ma, V Mezaris, B Ionescu, I Kompatsiaris, G Boato, N Sebe, ... Image and Vision Computing 53, 3-19, 2016 | 59 | 2016 |
| GLocal tells you more: coupling GLocal structural for feature selection with sparsity for image and video classification Y Yan, H Shen, G Liu, Z Ma, C Gao, N Sebe Computer Vision and Image Understanding 124, 99-109, 2014 | 58 | 2014 |
Alex HauptmannCarnegie Mellon UniversityEmail confirmado em cs.cmu.edu
